Lies Boelen

The fate and lifespan of human monocyte subsets in steady state and systemic inflammation

In humans, the monocyte pool comprises three subsets (classical, intermediate, and nonclassical) that circulate in dynamic equilibrium. The kinetics underlying their generation, differentiation, and disappearance are critical to understanding both steady-state homeostasis and inflammatory responses. Here, using human in vivo deuterium labeling, we demonstrate that classical monocytes emerge first from marrow, after a postmitotic interval of 1.6 d, and circulate for a day. Subsequent labeling of intermediate and nonclassical monocytes is consistent with a model of sequential transition. Intermediate and nonclassical monocytes have longer circulating lifespans (∼4 and ∼7 d, respectively). In a human experimental endotoxemia model, a transient but profound monocytopenia was observed; restoration of circulating monocytes was achieved by the early release of classical monocytes from bone marrow. The sequence of repopulation recapitulated the order of maturation in healthy homeostasis. This developmental relationship between monocyte subsets was verified by fate mapping grafted human classical monocytes into humanized mice, which were able to differentiate sequentially into intermediate and nonclassical cells.

Activity of a heptad of transcription factors is associated with stem cell programs and clinical outcome in acute myeloid leukemia

Aberrant transcriptional programs in combination with abnormal proliferative signaling drive leukemic transformation. These programs operate in normal hematopoiesis where they are involved in hematopoietic stem cell (HSC) proliferation and maintenance. Ets Related Gene (ERG) is a component of normal and leukemic stem cell signatures and high ERG expression is a risk factor for poor prognosis in acute myeloid leukemia (AML). However, mechanisms that underlie ERG expression in AML and how its expression relates to leukemic stemness are unknown. We report that ERG expression in AML is associated with activity of the ERG promoters and +85 stem cell enhancer and a heptad of transcription factors that combinatorially regulate genes in HSCs. Gene expression signatures derived from ERG promoter-stem cell enhancer and heptad activity are associated with clinical outcome when ERG expression alone fails. We also show that the heptad signature is associated with AMLs that lack somatic mutations in NPM1 and confers an adverse prognosis when associated with FLT3 mutations. Taken together, these results suggest that transcriptional regulators cooperate to establish or maintain primitive stem cell-like signatures in leukemic cells and that the underlying pattern of somatic mutations contributes to the development of these signatures and modulate their influence on clinical outcome.

Quantitative Analysis of Three-Dimensional Fluorescence Localization Microscopy Data

Identifying the three-dimensional molecular organization of subcellular organelles in intact cells has been challenging to date. Here we present an analysis approach for three-dimensional localization microscopy that can not only identify subcellular objects below the diffraction limit but also quantify their shape and volume. This approach is particularly useful to map the topography of the plasma membrane and measure protein distribution within an undulating membrane.

Transmission of Hepatitis C Virus among Prisoners, Australia, 2005-2012.

Ongoing transmission is associated with drug injection.

PDGF-AB and 5-Azacytidine induce conversion of somatic cells into tissue-regenerative multipotent stem cells

Significance In this report we describe the generation of tissue-regenerative multipotent stem cells (iMS cells) by treating mature bone and fat cells transiently with a growth factor [platelet-derived growth factor–AB (PDGF-AB)] and 5-Azacytidine, a demethylating compound that is widely used in clinical practice. Unlike primary mesenchymal stem cells, which are used with little objective evidence in clinical practice to promote tissue repair, iMS cells contribute directly to in vivo tissue regeneration in a context-dependent manner without forming tumors. This method can be applied to both mouse and human somatic cells to generate multipotent stem cells and has the potential to transform current approaches in regenerative medicine. Current approaches in tissue engineering are geared toward generating tissue-specific stem cells. Given the complexity and heterogeneity of tissues, this approach has its limitations. An alternate approach is to induce terminally differentiated cells to dedifferentiate into multipotent proliferative cells with the capacity to regenerate all components of a damaged tissue, a phenomenon used by salamanders to regenerate limbs. 5-Azacytidine (AZA) is a nucleoside analog that is used to treat preleukemic and leukemic blood disorders. AZA is also known to induce cell plasticity. We hypothesized that AZA-induced cell plasticity occurs via a transient multipotent cell state and that concomitant exposure to a receptive growth factor might result in the expansion of a plastic and proliferative population of cells. To this end, we treated lineage-committed cells with AZA and screened a number of different growth factors with known activity in mesenchyme-derived tissues. Here, we report that transient treatment with AZA in combination with platelet-derived growth factor–AB converts primary somatic cells into tissue-regenerative multipotent stem (iMS) cells. iMS cells possess a distinct transcriptome, are immunosuppressive, and demonstrate long-term self-renewal, serial clonogenicity, and multigerm layer differentiation potential. Importantly, unlike mesenchymal stem cells, iMS cells contribute directly to in vivo tissue regeneration in a context-dependent manner and, unlike embryonic or pluripotent stem cells, do not form teratomas. Taken together, this vector-free method of generating iMS cells from primary terminally differentiated cells has significant scope for application in tissue regeneration.

Signal analysis for genome-wide maps of histone modifications measured by ChIP-seq

MOTIVATION Chromatin structure, including post-translational modifications of histones, regulates gene expression, alternative splicing and cell identity. ChIP-seq is an increasingly used assay to study chromatin function. However, tools for downstream bioinformatics analysis are limited and are only based on the evaluation of signal intensities. We reasoned that new methods taking into account other signal characteristics such as peak shape, location and frequencies might reveal new insights into chromatin function, particularly in situation where differences in read intensities are subtle. RESULTS We introduced an analysis pipeline, based on linear predictive coding (LPC), which allows the capture and comparison of ChIP-seq histone profiles. First, we show that the modeled signal profiles distinguish differentially expressed genes with comparable accuracy to signal intensities. The method was robust against parameter variations and performed well up to a signal-to-noise ratio of 0.55. Additionally, we show that LPC profiles of activating and repressive histone marks cluster into distinct groups and can be used to predict their function. AVAILABILITY AND IMPLEMENTATION http://www.cancerresearch.unsw.edu.au/crcweb.nsf/page/LPCHP A Matlab implementation along with usage instructions and an example input file are available from: http://www.cancerresearch.unsw.edu.au/crcweb.nsf/page/LPCHP.

Bioinformatics analysis reveals biophysical and evolutionary insights into the 3-nitrotyrosine post-translational modification in the human proteome

Protein 3-nitrotyrosine is a post-translational modification that commonly arises from the nitration of tyrosine residues. This modification has been detected under a wide range of pathological conditions and has been shown to alter protein function. Whether 3-nitrotyrosine is important in normal cellular processes or is likely to affect specific biological pathways remains unclear. Using GPS-YNO2, a recently described 3-nitrotyrosine prediction algorithm, a set of predictions for nitrated residues in the human proteome was generated. In total, 9.27 per cent of the proteome was predicted to be nitratable (27 922/301 091). By matching the predictions against a set of curated and experimentally validated 3-nitrotyrosine sites in human proteins, it was found that GPS-YNO2 is able to predict 73.1 per cent (404/553) of these sites. Furthermore, of these sites, 42 have been shown to be nitrated endogenously, with 85.7 per cent (36/42) of these predicted to be nitrated. This demonstrates the feasibility of using the predicted dataset for a whole proteome analysis. A comprehensive bioinformatics analysis was subsequently performed on predicted and all experimentally validated nitrated tyrosine. This found mild but specific biophysical constraints that affect the susceptibility of tyrosine to nitration, and these may play a role in increasing the likelihood of 3-nitrotyrosine to affect processes, including phosphorylation and DNA binding. Furthermore, examining the evolutionary conservation of predicted 3-nitrotyrosine showed that, relative to non-nitrated tyrosine residues, 3-nitrotyrosine residues are generally less conserved. This suggests that, at least in the majority of cases, 3-nitrotyrosine is likely to have a deleterious effect on protein function and less likely to be important in normal cellular function.

Human Stem Cell-like Memory T Cells Are Maintained in a State of Dynamic Flux.

Summary Adaptive immunity requires the generation of memory T cells from naive precursors selected in the thymus. The key intermediaries in this process are stem cell-like memory T (TSCM) cells, multipotent progenitors that can both self-renew and replenish more differentiated subsets of memory T cells. In theory, antigen specificity within the TSCM pool may be imprinted statically as a function of largely dormant cells and/or retained dynamically by more transitory subpopulations. To explore the origins of immunological memory, we measured the turnover of TSCM cells in vivo using stable isotope labeling with heavy water. The data indicate that TSCM cells in both young and elderly subjects are maintained by ongoing proliferation. In line with this finding, TSCM cells displayed limited telomere length erosion coupled with high expression levels of active telomerase and Ki67. Collectively, these observations show that TSCM cells exist in a state of perpetual flux throughout the human lifespan.

Per-Event Probability of Hepatitis C Infection during Sharing of Injecting Equipment

Background Shared injecting apparatus during drug use is the premier risk factor for hepatitis C virus (HCV) transmission. Aims To estimate the per-event probability of HCV infection during a sharing event, and the transmission probability of HCV from contaminated injecting apparatus. Methods Estimates were obtained using a maximum likelihood method with estimated IDU and sharing events obtained from behavioural data. Settings Cohort study in multiple correction centres in New South Wales, Australia Participants Subjects (N = 500) with a lifetime history of injecting drug use (IDU) who were followed up between 2005 and 2012. During follow-up, interviews for risk behaviours were taken and blood sampling (HCV-antibody and RNA testing) was performed. Measurements Self-reported frequencies of injecting drugs and sharing events, as well as other risk behaviours and details on the nature of injecting events. Findings The best estimate of the per-event probability of infection was 0.57% (CI: 0.32–1.05%). A sensitivity analysis on the likely effect of under-reporting of sharing of the injecting apparatus indicated that the per event infection probability may be as low as 0.17% (95% CI: 0.11%–0.25%). The transmission probability was similarly shown to range up to 6%, dependent on the presumed prevalence of the virus in injecting equipment. Conclusions The transmission probability of HCV during a sharing event is small. Hence, strategies to reduce the frequency and sharing of injecting equipment are required, as well as interventions focused on decreasing the per event risk.

A Bayesian cluster analysis method for single-molecule localization microscopy data

Cell function is regulated by the spatiotemporal organization of the signaling machinery, and a key facet of this is molecular clustering. Here, we present a protocol for the analysis of clustering in data generated by 2D single-molecule localization microscopy (SMLM)—for example, photoactivated localization microscopy (PALM) or stochastic optical reconstruction microscopy (STORM). Three features of such data can cause standard cluster analysis approaches to be ineffective: (i) the data take the form of a list of points rather than a pixel array; (ii) there is a non-negligible unclustered background density of points that must be accounted for; and (iii) each localization has an associated uncertainty in regard to its position. These issues are overcome using a Bayesian, model-based approach. Many possible cluster configurations are proposed and scored against a generative model, which assumes Gaussian clusters overlaid on a completely spatially random (CSR) background, before every point is scrambled by its localization precision. We present the process of generating simulated and experimental data that are suitable to our algorithm, the analysis itself, and the extraction and interpretation of key cluster descriptors such as the number of clusters, cluster radii and the number of localizations per cluster. Variations in these descriptors can be interpreted as arising from changes in the organization of the cellular nanoarchitecture. The protocol requires no specific programming ability, and the processing time for one data set, typically containing 30 regions of interest, is ∼18 h; user input takes ∼1 h.